I am a third year undergraduate at Harvard University studying computer science and statistics. My interest is in applying machine learning and other computational methods to social science. In this blog, I mostly write about probability, statistics and machine learning.
Papers in progress.
- With Professor David Parkes on deep learning for understanding demand systems.
- With Professor Gary King on text based causal inference. (slide,preliminary paper)
- With Doctor Nir Rosenfeld on graph based semi-supervised learning (code, poster, preliminary paper).
- Scientific Programming (Python, R)
- Computing (Hadoop, Spark, Computing Clusters)
- Deployment (Docker, AWS, Heroku)
- Machine Learning (Scikit-Learn, Tensorflow, Pytorch)
- Web Programming (Rails, Flask)
- Mobile Programming (Swift)
- CS121 Theory of Computation
- CS124 Data Structures & Algorithms
- CS136 Economics and Computation
- CS181 Machine Learning
- CS236r Research in Economics and Computation
- CS281 Advanced Machine Learning
- CS282r Research in Robust Machine Learning
- Stat110 Probability
- Stat111 Inference
- Stat210 Probability Theory
- Stat286 Causal Inference
- AM221 Advanced Optimization
2– are graduate level courses —r are research focused seminar courses